{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = \"../data/train.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>cat0</th>\n",
       "      <th>cat1</th>\n",
       "      <th>cat2</th>\n",
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       "      <th>cat4</th>\n",
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       "      <th>cat6</th>\n",
       "      <th>cat7</th>\n",
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       "      <th>...</th>\n",
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       "      <th>cont6</th>\n",
       "      <th>cont7</th>\n",
       "      <th>cont8</th>\n",
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       "      <th>cont10</th>\n",
       "      <th>cont11</th>\n",
       "      <th>cont12</th>\n",
       "      <th>cont13</th>\n",
       "      <th>target</th>\n",
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       "  </thead>\n",
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       "      <td>0.741413</td>\n",
       "      <td>0.895799</td>\n",
       "      <td>0.802461</td>\n",
       "      <td>0.724417</td>\n",
       "      <td>0.701915</td>\n",
       "      <td>0.877618</td>\n",
       "      <td>0.719903</td>\n",
       "      <td>6.994023</td>\n",
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       "      <td>0.278495</td>\n",
       "      <td>0.593413</td>\n",
       "      <td>0.546056</td>\n",
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       "      <td>0.741289</td>\n",
       "      <td>0.326679</td>\n",
       "      <td>0.808464</td>\n",
       "      <td>8.071256</td>\n",
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       "    <tr>\n",
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       "      <td>A</td>\n",
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       "      <td>A</td>\n",
       "      <td>C</td>\n",
       "      <td>B</td>\n",
       "      <td>D</td>\n",
       "      <td>A</td>\n",
       "      <td>B</td>\n",
       "      <td>C</td>\n",
       "      <td>...</td>\n",
       "      <td>0.914155</td>\n",
       "      <td>0.369602</td>\n",
       "      <td>0.832564</td>\n",
       "      <td>0.865620</td>\n",
       "      <td>0.825251</td>\n",
       "      <td>0.264104</td>\n",
       "      <td>0.695561</td>\n",
       "      <td>0.869133</td>\n",
       "      <td>0.828352</td>\n",
       "      <td>5.760456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>A</td>\n",
       "      <td>A</td>\n",
       "      <td>A</td>\n",
       "      <td>C</td>\n",
       "      <td>B</td>\n",
       "      <td>D</td>\n",
       "      <td>A</td>\n",
       "      <td>E</td>\n",
       "      <td>G</td>\n",
       "      <td>...</td>\n",
       "      <td>0.934138</td>\n",
       "      <td>0.578930</td>\n",
       "      <td>0.407313</td>\n",
       "      <td>0.868099</td>\n",
       "      <td>0.794402</td>\n",
       "      <td>0.494269</td>\n",
       "      <td>0.698125</td>\n",
       "      <td>0.809799</td>\n",
       "      <td>0.614766</td>\n",
       "      <td>7.806457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>A</td>\n",
       "      <td>B</td>\n",
       "      <td>A</td>\n",
       "      <td>A</td>\n",
       "      <td>B</td>\n",
       "      <td>B</td>\n",
       "      <td>A</td>\n",
       "      <td>E</td>\n",
       "      <td>C</td>\n",
       "      <td>...</td>\n",
       "      <td>0.382600</td>\n",
       "      <td>0.705940</td>\n",
       "      <td>0.325193</td>\n",
       "      <td>0.440967</td>\n",
       "      <td>0.462146</td>\n",
       "      <td>0.724447</td>\n",
       "      <td>0.683073</td>\n",
       "      <td>0.343457</td>\n",
       "      <td>0.297743</td>\n",
       "      <td>6.868974</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   id cat0 cat1 cat2 cat3 cat4 cat5 cat6 cat7 cat8  ...     cont5     cont6  \\\n",
       "0   1    A    B    A    A    B    D    A    E    C  ...  0.881122  0.421650   \n",
       "1   2    B    A    A    A    B    B    A    E    A  ...  0.440011  0.346230   \n",
       "2   3    A    A    A    C    B    D    A    B    C  ...  0.914155  0.369602   \n",
       "3   4    A    A    A    C    B    D    A    E    G  ...  0.934138  0.578930   \n",
       "4   6    A    B    A    A    B    B    A    E    C  ...  0.382600  0.705940   \n",
       "\n",
       "      cont7     cont8     cont9    cont10    cont11    cont12    cont13  \\\n",
       "0  0.741413  0.895799  0.802461  0.724417  0.701915  0.877618  0.719903   \n",
       "1  0.278495  0.593413  0.546056  0.613252  0.741289  0.326679  0.808464   \n",
       "2  0.832564  0.865620  0.825251  0.264104  0.695561  0.869133  0.828352   \n",
       "3  0.407313  0.868099  0.794402  0.494269  0.698125  0.809799  0.614766   \n",
       "4  0.325193  0.440967  0.462146  0.724447  0.683073  0.343457  0.297743   \n",
       "\n",
       "     target  \n",
       "0  6.994023  \n",
       "1  8.071256  \n",
       "2  5.760456  \n",
       "3  7.806457  \n",
       "4  6.868974  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(path)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id        0\n",
       "cat0      0\n",
       "cat1      0\n",
       "cat2      0\n",
       "cat3      0\n",
       "cat4      0\n",
       "cat5      0\n",
       "cat6      0\n",
       "cat7      0\n",
       "cat8      0\n",
       "cat9      0\n",
       "cont0     0\n",
       "cont1     0\n",
       "cont2     0\n",
       "cont3     0\n",
       "cont4     0\n",
       "cont5     0\n",
       "cont6     0\n",
       "cont7     0\n",
       "cont8     0\n",
       "cont9     0\n",
       "cont10    0\n",
       "cont11    0\n",
       "cont12    0\n",
       "cont13    0\n",
       "target    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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